Projekt

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Dynamic Mesh Compression

Gesuchsteller/in Hormann Kai
Nummer 146764
Förderungsinstrument Projektförderung (Abt. I-III)
Forschungseinrichtung Facoltà di scienze informatiche Università della Svizzera italiana
Hochschule Università della Svizzera italiana – USI
Hauptdisziplin Informatik
Beginn/Ende 01.05.2013 - 30.04.2014
Bewilligter Betrag 91'350.00
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Keywords (4)

Geometry Processing; Computer Graphics; Dynamic Geometry; Mesh Compression

Lay Summary (Deutsch)

Lead
Die geometrische Modellierung ist der Teilbereich der Computergrafik, der sich mit Beschreibung und Verarbeitung statischer 3D-Flächen beschäftigt. Einige Anwendungen (z. B. Animation, Simulation) basieren aber auf dynamischen 3D-Flächen, also Flächen, deren Geometrie sich in Abhängigkeit eines Zeitparameters ändert. Anstatt einen solchen Datensatz als eine endliche Menge statischer 3D-Flächen zu betrachten, ist es vorteilhaft, ihn als eine 4D-Fläche anzusehen und temporale Kohärenz auszunutzen.
Lay summary
Das Hauptziel dieses Projekts ist, effiziente Verfahren zur kompakten, verlustbehafteten Speicherung dynamischer Dreiecksnetze zu entwickeln. Während bisherige Verfahren zur Komprimierung solcher Daten auf der Darstellung der Dreiecksnetze im euklidischen Raum basieren, werden wir untersuchen, inwieweit alternative Darstellungen zur Qualität der Kompression beitragen können. Insbesondere werden wir Kanten-basierte Modelle betrachten, bei denen ein Dreiecksnetz implizit durch die Längen seiner Kanten und die dihedralen Winkel an den Kanten gespeichert ist. Im Detail werden wir (i) single-rate und (ii) progressive Kompressionstechniken studieren und (iii) eine neue Methode entwickeln, die auf einer vorherigen Segmentierung des Netzes in bewegliche und starre Teilnetze basiert. Zur objektiven Beurteilung der Qualität der Resultate werden wir zudem neue Fehlermaße konstruieren, die den Abstand zwischen den Originaldaten und den rekonstruierten Daten.
Direktlink auf Lay Summary Letzte Aktualisierung: 27.03.2013

Verantw. Gesuchsteller/in und weitere Gesuchstellende

Mitarbeitende

Name Institut

Publikationen

Publikation
Exploring Compression in Edge Shape Space
Marras Stefano, Hormann Kai (2015), Exploring Compression in Edge Shape Space, Faculty of Informatics, Università della Svizzera italiana, Lugano.
Compressing dynamic meshes with geometric Laplacians
Váša Libor, Marras Stefano, Hormann Kai, Brunnett Guido (2014), Compressing dynamic meshes with geometric Laplacians, in COMPUTER GRAPHICS FORUM, 33(2), 145-154.
Perception-driven adaptive compression of static triangle meshes
Marras Stefano, Váša Libor, Brunnett Guido, Hormann Kai, Perception-driven adaptive compression of static triangle meshes, in COMPUTER-AIDED DESIGN.

Zusammenarbeit

Gruppe / Person Land
Formen der Zusammenarbeit
Dr. Ing. Libor Váša, TU Chemnitz Deutschland (Europa)
- vertiefter/weiterführender Austausch von Ansätzen, Methoden oder Resultaten
- Publikation
- Austausch von Mitarbeitern

Verbundene Projekte

Nummer Titel Start Förderungsinstrument
134639 Interactive Modelling of Dynamics 3D Surfaces 01.05.2011 Projektförderung (Abt. I-III)
134639 Interactive Modelling of Dynamics 3D Surfaces 01.05.2011 Projektförderung (Abt. I-III)

Abstract

The interdisciplinary research area of geometry processing combines concepts from informatics, applied mathematics, and engineering for the efficient acquisition, reconstruction, optimization, editing, and simulation of geometric objects. Applications of geometry processing algorithms can be found in a wide range of areas, including computer graphics, computer aided design, geography, and scientific computing. Moreover, this research field enjoys a significant economic impact as it delivers essential ingredients for the production of cars, airplanes, movies, and computer games, for example.Over the last years, a novel trend has emerged within this field, which concentrates on time-varying geometry. As opposed to classical processing of static 3D surfaces, the new goal is to develop algorithms for efficiently handling dynamic 3D surfaces, which frequently occur in applications like character animation or physical simulations. These kind of 4D objects are most commonly represented as a discrete sequence of frames, each of which is given as a mesh with a common graph structure. Such sequences have the flexibility to represent a wide range of mesh deformations used in practice, but they are also highly redundant and expensive to store. Hence, there is a great need for dynamic mesh compression algorithms.While common methods for compressing mesh sequences rely on the meshes being stored in terms of vertex coordinates, the aim of this project is to develop lossy compression algorithms based on an alternative mesh representation in an edge-based shape space, that is, by storing lengths and dihedral angles for all edges. This approach is motivated by the observation that these quantities vary comparatively little over time, in particular for the rigid parts of an animated character. We plan to further investigate this behaviour, to provide a better understanding of the underlying principles, and to turn our findings into efficient algorithms for encoding and decoding sequences of meshes. We expect our results to considerably advance the state of the art in this field and to have an impact on related geometry processing algorithms which may benefit from an edge-based mesh representation.In particular, we will address the following problems: First, we will explore the setting of single-rate compression, where each frame of the sequence must be fully decoded before decoding the next one. Second, we will consider a progressive approach, where the sequence is considered at different levels of detail and the compression algorithm takes advantage of this multi-resolution representation. Third, we plan to develop a technique that is based on a segmentation of the dynamic mesh into rigid and non-rigid parts and is therefore particularly tailored for compressing character animations. A key ingredient to all these approaches is to have an efficient method at hand for converting meshes from the edge-based representation back into usual vertex coordinates. Currently, two methods exist for performing this operation, both with advantages and disadvantages, and we want to design a hybrid approach that combines the positive aspects of the two methods. Finally, we will also focus on the problem of measuring the distance between a given mesh sequence and its reconstructed counterpart, so as to be able to properly evaluate the results of lossy compression algorithms, as well as to optimize their performance. Recent results reveal that edge-based error measures capture visually perceived artefacts better than vertex-based variants, and we want to further explore the use of such error measures which naturally fit our approach of working with edge-based mesh representations.
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